Periodontal disease and endometriosis: analysis of the National Health and Nutrition Examination Survey

Periodontal disease and endometriosis: analysis of the National Health and Nutrition Examination Survey Shahryar K. Kavoussi, M.D., M.P.H.,a Brady T. West, M.A.,b George W. Taylor, D.M.D., Dr.P.H.,c and Dan I. Lebovic, M.D., M.A.a a Department of Obstetrics and Gynecology, Division of Reproductive Endocrinology and Infertility, University of Michigan Endometriosis Center, University of Michigan Health System; b Center for Statistical Consultation and Research, University of Michigan; and c Department of Cardiology, Restorative Sciences and Endodontics, University of Michigan School of Dentistry, Ann Arbor, Michigan

Objective: To investigate whether an association exists between endometriosis and periodontal disease, because endometriosis and periodontal disease are chronic, inflammatory processes more common in patients with systemic autoimmune disorders and because each disease alters immune modulators. Design: Cross-sectional study. Setting: University health system and statistical center. Patient(s): Data for 4136 women, ages 18–50, in the National Health and Nutrition Examination Survey, 1999– 2004. Intervention(s): None. Main Outcome Measure(s): Periodontitis and gingivitis among those patients with and without self-reported endometriosis. Result(s): Multinomial logistic regression showed that women with self-reported endometriosis had significantly (57%) higher odds of having both gingivitis and periodontitis relative to not having periodontal disease, compared with women without self-reported endometriosis (adjusted odds ratio, 1.57; 95% confidence interval, 1.06, 2.33), when controlling for other relevant factors. Conclusion(s): The results of this study suggest a possible association between endometriosis and periodontal disease. Although it is conceivable that the multifactorial development of endometriosis may be augmented by an immune response to an infectious agent, the potential underlying link between endometriosis and periodontal disease may be a generalized, global immune dysregulation. (Fertil Steril 2009;91:335–42. 2009 by American Society for Reproductive Medicine.) Key Words: Endometriosis, periodontal disease, periodontitis, gingivitis, inflammation, autoimmune, NHANES

Endometriosis, a potential cause of pelvic pain and infertility, affects 6%–10% of reproductive-age women (1) and is characterized by the presence of endometrial glands and stroma located outside the uterine cavity. It is thought that among the multifactorial genesis and persistence of ectopic endometriotic tissue, one contributing factor is a defect in the immune system’s ability to clear (2) retrograde menstrual effluent (3). The immunobiology of endometriosis represents a paradigm shift in theories of the pathogenesis of endometriosis (2, 4).

and diabetes (6), with which periodontal disease has a bidirectional relationship (6). As is the case for endometriosis, autoimmunity has been implicated in the pathogenesis of periodontal disease (7).

Periodontal disease is a chronic inflammatory disorder as well. It includes the milder variant gingivitis, which is a reversible inflammation of the soft tissues adjacent to the teeth, and periodontitis, the more severe form of the disease, which essentially is the destruction of soft tissues, alveolar bone, and the other supporting structures of the dentition (5). Approximately 50% of U.S. adults have gingivitis, 30% have some degree of periodontitis, and 5%–15% have severe periodontal disease (5). Major risk factors include smoking (5)

Since both endometriosis and periodontal disease are chronic, inflammatory processes that are more common in those patients who have systemic autoimmune disorders and since both have been found to alter immune modulators, the aim of this study was to investigate whether or not an association exists between endometriosis and periodontal disease. Investigators have suggested that the relationship between periodontal disease and systemic autoimmune disorders may be that of cause and effect, respectively, due to an inflammatory response to seeded periodontal bacterial pathogens. Although a causeand-effect relationship cannot be ruled out in the case of endometriosis and periodontal disease, we sought to investigate a potential association between the two diseases that could be a sign of a global immune dysregulation.

Received October 13, 2007; revised and accepted December 20, 2007. Supported by National Institutes of Health grant nos. 5K23HD043952-02 (to DIL) and T32 HD070048 (to SK). Reprint requests: Dan I. Lebovic, M.D., M.A., L4100 Women’s Hospital, 1500 East Medical Center Drive, Ann Arbor, MI 48109-0276 (FAX: 734-647-1006; E-mail: [email protected]).

MATERIALS AND METHODS Study Design Data source A cross-sectional study was performed using 6 years of data (1999–2004) from the National Health and

0015-0282/09/$36.00 doi:10.1016/j.fertnstert.2007.12.075

Fertility and Sterility Vol. 91, No. 2, February 2009 Copyright ª2009 American Society for Reproductive Medicine, Published by Elsevier Inc.

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Nutrition Examination Survey (NHANES), which was administered by the National Center for Health Statistics (NCHS) as a combination of patient interviews and physical examinations designed to assess the health and nutritional status of the U.S. population. In each of three independent 2-year NHANES samples (1999–2000, 2001–2002, and 2003–2004), information was collected from nationally representative U.S. samples of persons on a variety of measures. These measures were grouped into four different categories of data sets for each 2-year sample: demographics, questionnaire items (e.g., reproductive health, diabetes history), physical examination measurements (e.g., periodontal health), and laboratory measures (e.g., serum cotinine levels). In the present study, only those sampled women having measures collected on each of several variables of research interest from the demographic, examination, laboratory, and questionnaire data files in each 2-year sample were included for a secondary analysis. The women having all of these measures collected in each 2-year sample were merged into a single data set for analysis. The merged data set, which included sample records from 1999–2004 for women surveyed on all variables of interest, yielded 4947 women, and the subpopulation of interest for the study consisted of 4136 of these women who were ages 18–50 (a range deemed by the investigators to represent reproductive ages). Because the NHANES was not specifically designed to collect complete data on all of the measures of interest for this particular study (i.e., not all sampled individuals were given a full physical examination, and some individuals did not respond to the questionnaires) and because some individuals simply did not have complete data for the analysis variables, multiple-imputation (8) was used to analyze the data and assess the robustness of results based on only those sample women with complete data (see the Statistical Analysis section). These analyses did not require University of Michigan Institutional Review Board (IRB) approval because the research was a secondary analysis of a publicly available data set. Under federal regulations for human subjects research (45 CFR Part 46), IRB review of analysis of publicly available data sets that are stripped of identifiers is not required. Sampling weights Because individual women had to have a full physical examination to be included in the analysis sample for the present study, sampling weights computed by NCHS staff to reflect [1] unequal probability of selection into the original NHANES sample, [2] subsequent unequal probability of having a physical examination, and [3] other factors, such as survey nonresponse and adjustment to population controls, were incorporated in the analyses per NHANES documentation (9) to ensure that statistical estimates of desired parameters would be nationally representative of the subpopulation of interest (women ages 18– 50). The analysis sample for the present study can be considered as a cross-sectional sample of U.S. women from the years 1999–2004. Per NHANES guidelines for calculating 336

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nationally representative statistical estimates from this 6-year time period, the sampling weights provided by NCHS staff for each sample respondent given a physical examination were adjusted so that estimates would represent the 6-year time period, rather than 2- or 4-year time periods (9). Measures The periodontal health status outcome variable was specified in two ways: healthy versus any periodontal disease (i.e., either gingivitis or periodontitis) and as a fourcategory outcome (i.e., healthy, gingivitis only, periodontitis only, or gingivitis and periodontitis). The data to define the periodontal health status outcome were derived from clinical oral health examination data collected for probing pocket depths, gingival bleeding, and clinical attachment levels based on random half-mouth evaluations. The data from the 1999–2000 NHANES included probing assessments for pocket depths and attachment level at two sites per tooth and a quadrant-level gingival bleeding indicator for gingivitis. For the 2001–2004 NHANES data, three sites per tooth were assessed for probing pocket depth and attachment level, and each tooth was individually evaluated for gingival bleeding. An outcome of ‘‘gingivitis only’’ was defined as one or more quadrants or one or more sites with gingival bleeding and no periodontitis. An outcome of ‘‘periodontitis’’ was defined as one or more teeth with one or more sites having a probing pocket depth of 4 mm or greater and attachment loss greater than or equal to 2 mm (8). Individuals with neither gingivitis nor periodontitis were considered to have healthy periodontal status. The principal exposure variable, indicating history of endometriosis, was derived from the interview response to the question of whether the woman was told by a physician that she had endometriosis. There were no additional indicators for a history of endometriosis in the NHANES database. Additional explanatory variables evaluated in this study included established risk factors or indicators for periodontal disease and variables considered to confound or modify the effect of endometriosis. The risk factors/indicators associated with periodontal disease included age (18–29, 30–39, 40þ), race/ethnicity (Mexican-American, other Hispanic, nonHispanic black, non-Hispanic white, and other racial/ethnic groups), education (less than high school, high school diploma, or education beyond high school diploma), household income ($0–$19,999, $20,000–$44,999, $45,000–74,999, $75,000þ), smoking status based on serum cotinine (>15 ng/mL) (10, 11), and diabetes (defined as either a self-reported history of diabetes diagnosis by a physician or other health provider, taking insulin or oral hypoglycemic agent, or having fasting plasma glucose of 126 mg/dL or greater; cases classified as ‘‘borderline’’ in the NHANES data were set to missing). Other covariates associated with endometriosis included age at first period (in years 8–11, 12, 13, or 14 or more), parity (0, 1, 2, 3 or more), and current pregnancy status (pregnant or not pregnant determined by self-report on the reproductive health questionnaire in conjunction with a serum beta-hCG assay). Vol. 91, No. 2, February 2009

Statistical Analysis Complete-case analyses Initial analyses performed on the 4136 women in the analysis subpopulation were conducted by excluding respondents with missing data on any of the analysis variables. Weighted statistical estimates of the percentage of respondents in the subpopulation of women having certain values on the analysis variables were initially computed to provide a descriptive summary of the subpopulation of interest represented by the analysis subsample. Binary logistic and multinomial logistic regression analyses were then performed considering only those cases with complete data on all measures to estimate the relationships of endometriosis with the binary periodontal health status outcome (no gingivitis or periodontitis vs. gingivitis or periodontitis) and the four-category dental health outcome, while controlling for the relationships of other relevant predictors with the periodontal status outcomes. Because of the exploratory nature of this analysis, a backward selection technique was used when fitting the regression models, to determine the subsets of predictors having significant associations with each outcome. In each analysis, Taylor series linearization was used to compute SEs for the statistical estimates incorporating the stratified and clustered design features of the NHANES samples and providing information about the sampling error associated with the estimates. Because the 4136 women represent a sample from the subpopulation of women between the ages of 18 and 50, methods appropriate for subpopulation analyses (12) were applied to ensure that the full-complex designs of the NHANES samples were taken into account for calculation of robust SEs. All completecase analyses were performed using procedures in the SAS (version 9.1.3; SAS Institute Inc., Cary, NC) and SUDAAN (version 9.0.1; RTI International, Research Triangle Park, NC) software packages designed for the analysis of complex sample survey data. Multiple-imputation analyses Because the analysis sample for the multivariate analyses (e.g., binary logistic regression) was reduced by roughly 50% because of missing data on the individual analysis variables (the variable with the most missing data was parity, with 1206 of the 4136 women missing data), multiple-imputation analysis was used to examine whether results based on the complete-case analyses remained stable after imputation of missing values and to allow for more statistical power to detect relationships of interest between the analysis variables. The sequential regression imputation method was used in the IVEware software package (Institute for Social Research, Ann Arbor, MI) to generate five complete data sets with all missing values imputed (with n ¼ 4947 having complete data), and the same analyses that were described above for the complete cases were once again performed on each of the five imputed data sets. The results from the five sets of analyses were then combined per the methodology described by Little and Rubin (13) to generate a final overall set of multiple-imputation estimates for each analysis, reflecting both within- and betweenimputation variance in the statistical estimates. The overall multiple-imputation estimates were compared with the comFertility and Sterility

plete-case estimates to determine whether the results changed substantively after multiple imputations of the missing data. RESULTS The results in Table 1 indicate that the subpopulation of women, aside from being ages 18–50 years, is estimated to be 66% white, 59% well-educated (more than a high school degree), well-represented in each of the income categories, more than 50% married, and 50% healthy in terms of periodontal health status; more than 90% have never had endometriosis, 73% have a low cotinine level, only 8% have never had a child, and 94% are not currently pregnant. In addition, the prevalence of diabetes is under 3%. We also note that the process of multiple imputation did not change the subpopulation estimates substantially and provided complete data sets for the multivariable analyses. Results from fitting the binary logistic regression model to the outcome broadly measuring periodontal health status (any periodontal disease vs. healthy) are presented in Table 2, before and after multiple imputations of the missing data. In the complete-case analyses, the following predictors were not found to have a significant relationship with periodontal disease in design-based Wald tests and were dropped from the model: diabetes, age at first period, high serum cotinine, age, and the parity indicator. After dropping these predictors, all other covariates with the exception of endometriosis (education, ethnicity, income, and pregnancy) had a statistically significant (P<.05) association with the outcome in the complete-case analysis. Because of missing data, only 2052 observations (out of 4136) were used to fit the initial model in the complete-case analysis, and only 2804 observations were used to fit the subsequent reduced model. The same reduced model was fit when performing the multiple-imputation analyses, and endometriosis was found to have a marginally significant association with the binary outcome. The results of the multivariable analyses presented in Table 2 indicate that, in general, white women in this subpopulation have the lowest odds of having poorer periodontal health (for example, Mexican-American women are estimated to have between 76% [multiple-imputation analysis] and 84% [complete-case analysis] higher odds of having any periodontal disease compared with white women). In addition, higher income and higher education result in lower odds of having a poor outcome, while being pregnant increases the odds of having a poor outcome by roughly 40%–50%. We note that endometriosis has a marginally significant association with the odds of having a poor outcome based on the multiple-imputation analysis, where women who have been told that they have endometriosis have 31% higher odds of having a poor outcome (adjusted odds ratio [AOR], 1.31; 95% confidence interval [CI], 0.91, 1.88). Table 3 presents results from fitting the multinomial logistic regression model to the outcome measuring the four specific categories of dental health in the complete-case analysis. Wald tests of the independent predictors in the complete-case 337

TABLE 1 Weighted estimates of frequency distributions for the analysis variables, for the subpopulation of interest (before and after multiple imputations of item-missing values). Analysis variable Ethnicity: Mexican-American Hispanic White Black Other Education: Less than high school High school diploma More than high school Income, $: 0–19,999 20,000þ 20,000–44,999 45,000–74,999 75,000þ Periodontal health status: Healthy Any periodontal disease Gingivitis only Periodontitis only Gingivitis and periondontitis Ever had endometriosis? Yes No High cotinine (>15 ng/mL)? Yes No Age at first period, years: 8–11 12þ 12 13 14þ Parity: 0 1þ 1 2 3þ Pregnancy: Currently pregnant Not pregnant Diabetes?c Yes No

n (Preimputation)

Weighted, % (SE)

n (Postimputation)a

Weighted, % (SE)b

1022 223 1836 882 173

8.66 (0.95) 6.84 (1.31) 66.06 (1.91) 13.30 (1.19) 5.14 (0.63)

1022 223 1836 882 173

8.66 (0.95) 6.84 (1.31) 66.06 (1.91) 13.30 (1.19) 5.14 (0.69)

1067 961 2104

16.97 (0.81) 24.21 (1.04) 58.81 (1.38)

1068 962 2106

16.98 (0.81) 24.23 (1.04) 58.80 (1.38)

827 2922 1183 836 903

18.23 (0.88) 81.77 (0.88) 29.22 (1.36) 23.70 (0.90) 28.84 (1.53)

847 3289 1319 915 1055

17.26 (0.85) 82.75 (0.85) 29.33 (1.35) 23.49 (0.87) 29.92 (1.51)

1466 1865 1154 168 543

49.85 (2.56) 50.15 (2.56) 31.32 (1.68) 5.58 (0.60) 13.25 (1.42)

1824 2312 1412 230 670

49.33 (2.31) 50.67 (2.31) 31.16 (1.54) 5.94 (0.68) 13.57 (1.32)

235 3442

8.67 (0.71) 91.33 (0.71)

263 3873

8.61 (0.73) 91.39 (0.73)

869 2955

26.60 (1.14) 73.40 (1.14)

946 3190

26.75 (1.15) 73.25 (1.15)

834 2774 969 901 904

22.26 (0.82) 77.74 (0.82) 26.81 (1.02) 26.54 (0.93) 24.39 (0.69)

944 3192 1114 1048 1030

22.16 (0.81) 77.84 (0.81) 26.85 (0.96) 26.70 (0.88) 24.29 (0.69)

195 2735 779 931 1025

7.62 (0.80) 92.38 (0.80) 24.64 (1.07) 35.64 (1.18) 32.10 (1.15)

263 3873 1130 1427 1317

7.14 (0.91) 92.86 (0.91) 25.39 (1.15) 38.30 (1.16) 29.18 (1.17)

765 3294

6.04 (0.37) 93.96 (0.37)

778 3358

6.29 (0.40) 93.71 (0.40)

150 3957

2.96 (0.29) 97.04 (0.29)

152 3984

2.99 (0.30) 97.01 (0.30)

a

n ¼ 4136 in the case of each variable. Based on the results of a multiple-imputation analysis with M ¼ 5 imputed datasets. c Cases coded as ‘‘borderline’’ are set to missing and eligible for imputation. b

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TABLE 2 Weighted estimates of AORs and design-based 95% CIs, indicating the association of endometriosis with the binary periodontal health status outcome (before and after multiple imputations), in addition to all other statistically significant associations. Predictor

Complete-case analysisa AOR (95% CI)

Multiple-imputation analysisb AOR (95% CI)

1.20 (0.84, 1.72) REF

1.31 (0.91, 1.88) REF

1.56 (1.09, 2.24) 1.54 (1.23, 1.92) REF

1.56 (1.16, 2.11) 1.46 (1.22, 1.74) REF

1.84 (1.27, 2.67) 1.33 (0.87, 2.04) REF 1.56 (1.14, 2.12) 1.75 (1.07, 2.87)

1.76 (1.33, 2.34) 1.52 (1.08, 2.14) REF 1.49 (1.16, 1.93) 1.66 (1.18, 2.33)

REF 0.66 (0.50, 0.87)

REF 0.71 (0.55, 0.93)

1.40 (1.01, 1.93) REF

1.50 (1.14, 1.99) REF

Endometriosis? Yes No Education: Less than high school High school Diploma More than high school Race/ethnicity: Mexican-American Hispanic White Black Other Income, $: 0–19,999 20,000þ Pregnancy status: Currently pregnant Not pregnant Note: REF ¼ reference category. a Subpopulation n ¼ 2804. b Subpopulation n ¼ 4136; M ¼ 5 imputations.

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analysis revealed that the following predictors should be dropped from the model because of a lack of significance (P<.10): age at first period, diabetes, and the parity indicator. The design-based Wald test for the endometriosis indicator in the reduced model indicated that endometriosis had a statistically significant association with the four-category outcome (Wald test, P<.0189) when controlling for the relationships of the other significant predictors with the outcome in the complete-case analysis. Specifically, the results showed that women with endometriosis had significantly (57%) higher odds of having gingivitis and periodontitis relative to not having periodontal disease, compared with women without endometriosis (AOR, 1.57; 95% CI, 1.06, 2.33). Because of missing data, only 2052 observations (out of 4136) were used to fit the initial model, and only 2664 observations were used to fit the reduced model. The results from the multivariable analysis presented in Table 3 suggest other meaningful associations based on the cases with complete data. In general, lower education levels increase the risk of having adverse outcomes; younger women have higher odds of having gingivitis only relative to being healthy; white women again have reduced odds of having adverse outcomes; higher income tends to result in lower odds of having adverse outcomes; higher cotinine Fertility and Sterility

levels tend to increase the odds of having adverse outcomes; and currently being pregnant tends to increase the odds of having adverse outcomes as well. The results based on the analysis of the complete data set (throwing out cases with missing data) were essentially replicated in the multiple-imputation analyses, suggesting that the findings are robust. Specifically, the risk of having both adverse outcomes relative to being healthy was found to be increased by 44% after controlling for the relationships of the other predictors in Table 3 with the four-category outcome (AOR ¼ 1.44; 95% CI, 0.92, 2.25). Even after using a statistically valid technique to impute the missing values (14), we have essentially the same findings, only we used a complete data set rather than one with 50% of the cases lost because of missing data. This suggests the findings would remain stable in an even larger sample. DISCUSSION The results of this study provide evidence of a statistically meaningful association between endometriosis and periodontal disease after adjusting for other relevant predictors of periodontal disease. Specifically, the odds of having both gingivitis and periodontitis relative to being healthy were 339

TABLE 3 Weighted estimates of AORs and design-based 95% CIs, indicating the association of endometriosis with the four-category periodontal health status outcome (in the complete-case analysis, before multiple imputations), in addition to all other statistically significant associations. Predictor Endometriosis?b Yes No Educationc: Less than high school High school diploma More than high school Age group, yearsc: 18–29 30–39 40þ Race/ethnicityc: Mexican-American Hispanic White Black Other Incomec: 0–19,999 20,000þ Cotininec: <15 ngmL R15 ngmL Pregnancy statusa: Currently pregnant Not pregnant

Gingivitis Only AOR, 95% CI

Periodontitis Only AOR, 95% CI

Gingivitis and Periodontitis AOR, 95% CI

1.26 (0.83, 1.91) REF

0.42 (0.13, 1.34) REF

1.57 (1.06, 2.33) REF

1.28 (0.83, 1.97) 1.33 (1.04, 1.70) REF

2.57 (1.61, 4.11) 1.92 (1.13, 3.26) REF

1.62 (0.95, 2.74) 1.65 (1.03, 2.66) REF

1.58 (1.16, 2.17) 1.40 (1.08, 1.82) REF

0.73 (0.41, 1.30) 0.84 (0.45, 1.54) REF

0.62 (0.38, 1.02) 0.75 (0.51, 1.11) REF

1.77 (1.23, 2.55) 1.28 (0.84, 1.96) REF 1.19 (0.81, 1.73) 1.86 (1.09, 3.15)

1.03 (0.56, 1.88) 1.04 (0.38, 2.87) REF 1.06 (0.63, 1.80) 1.68 (0.58, 4.84)

2.76 (1.57, 4.86) 1.47 (0.64, 3.34) REF 2.78 (1.79, 4.31) 1.74 (0.74, 4.11)

REF 0.70 (0.48, 1.01)

REF 0.65 (0.36, 1.17)

REF 0.58 (0.42, 0.79)

REF 0.86 (0.63, 1.18)

REF 1.45 (0.92, 2.28)

REF 1.44 (0.95, 2.17)

1.19 (0.83, 1.69) REF

1.35 (0.72, 2.50) REF

1.77 (1.09, 2.89) REF

Note: Baseline outcome category ¼ healthy. Subpopulation n ¼ 2664 (complete data); REF ¼ reference category. a P< .10 based on design-adjusted Wald test. b P< .05 based on design-adjusted Wald test. c P< .01 based on design-adjusted Wald test. Kavoussi. Periodontal disease and endometriosis . Fertil Steril 2009.

increased by 57% if a woman had been told that she had endometriosis, when controlling for the relationships of the other predictors with the periodontal health status outcome. That is to say, among a population of 100 women suffering from gingivitis and periodontitis, 61 will have the additional disease burden of endometriosis while the remaining 39 will not (Fig. 1A). Although endometriosis and periodontal disease affect different systems and traditionally have appeared to be unrelated, each disease process is characterized as a chronic, inflammatory disorder that is associated with an altered immune response (Fig. 1B). This so-called global immune dysregulation could account for the increased incidence of other systemic, autoimmune disorders for each ailment. For example, systemic lupus erythematosus and rheumatoid arthritis as well as other autoimmune inflammatory conditions, hypothy340

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roidism, allergies, fibromyalgia, asthma, and multiple sclerosis are more common in women with endometriosis (15, 16). In parallel, associations have been found between periodontal disease and systemic disorders such as diabetes mellitus (8, 17), cardiovascular disease (18–20), pulmonary disease (21–23), and preterm delivery (22, 24–29). Furthermore, endometriosis and periodontal disease have each been shown to be associated with altered levels of immune modulators. Specifically, the presence of endometriotic lesions has been associated with decreased natural killer cell activity and cytotoxicity against endometrial cells (2, 30, 31) as well as increased levels of sICAM-1, peripheral monocytes, peritoneal macrophages, and lymphocytes. In addition, increased levels of cytokines and factors such as IL (interleukin)-1b, IL-6, IL-8, tumor necrosis factor-a (TNF-a), vascular endothelial growth factor, RANTES (regulated upon Vol. 91, No. 2, February 2009

FIGURE 1 (A) Pie chart showing the main finding from this NHANES study, namely, a greater incidence of periodontal disease among those with self-reported endometriosis (61%) when compared with those without self-reported endometriosis (39%). POD ¼ periodontal disease; Osis ¼ endometriosis.(B) Putative causation Venn diagram illustrating the concept of baseline chronic inflammation causing periodontal disease (or vice versa) as well as endometriosis (or vice versa).

Kavoussi. Periodontal disease and endometriosis . Fertil Steril 2009.

activation, normal T cell expressed and secreted), and monocyte chemoattractant protein-1 have been demonstrated in the peritoneal fluid of women with endometriosis (32–39). Chronic periodontitis is linked to a chronic systemic inflammatory burden secondary to the systemic dissemination of periodontal pathogenic bacteria, their products (e.g., lipopolysaccharides), and locally produced inflammatory mediators (i.e., IL-1b, IL-6, TNF-a, prostaglandin E2, and thromboxane B2) (40–42). As with most population-based surveys, NHANES was not specifically designed to address the topic of this study, and missing data are a potential limitation. The use of multiple-imputation procedures in the analyses tempered this limitation. The results support the value of future focused investigations on this topic with data collection directed toward eliminating missing data on the specific variables of interest in assessing the suggested relationships identified. In addition, NHANES measures used to define the presence and/or degree of this study’s diseases of interest inherently pose limitations. Examples include the relative inaccuracy of the self-reporting of endometriosis as compared with data indicating laparoscopic findings and the differences in the literature in regards to variables used to create periodontal disease indicators. Another limitation of NHANES is that the dental examination data were derived from random halfmouth examinations, measuring two or three sites per tooth rather than the six sites used in full-mouth periodontal examinations. The NHANES periodontal examination procedure is recognized to underestimate the prevalence of periodontal disease (43, 44). This underestimation would lead to nondifferential misclassification among those patients with and without endometriosis, attenuating the strength of the association identified in the analysis and therefore suggesting that the associations identified in this study may be even stronger than reported here. Fertility and Sterility

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